The genetic bases of neuropsychiatric disorders are beginning to yield to scientific inquiry. Genome-wide studies of copy number variation (CNV) have given rise to a new understanding of disease etiology, bringing rare variants to the forefront. A proportion of risk for schizophrenia, bipolar disorder and Autism can be explained by rare mutations. Such alleles arise by de novo mutation in the individual or in recent ancestry. Alleles can have specific effects on behavioral and neuroanatomical traits; however expressivity is variable, particularly for neuropsychiatric phenotypes. Knowledge from CNV studies reflects the nature of rare alleles in general and will serve as a guide as we move forward into a new era of whole genome sequencing.

Detecting genomic structural variants from high-throughput sequencing data is a complex and unresolved challenge. We have developed a statistical learning approach, based on Random Forests, which integrates prior knowledge about the characteristics of structural variants and leads to improved discovery in high throughput sequencing data. The implementation of this technique, forestSV, offers high sensitivity and specificity coupled with the flexibility of a data-driven approach.

SUMMARY

Schizophrenia (SCZD) is a debilitating neurological disorder with a world-wide prevalence of 1%; there is a strong genetic component, with an estimated heritability of 80–85%1. Though postmortem studies have revealed reduced brain volume, cell size, spine density and abnormal neural distribution in the prefrontal cortex and hippocampus of SCZD brain tissue2 and neuropharmacological studies have implicated dopaminergic, glutamatergic and GABAergic activity in SCZD3, the cell types affected in SCZD and the molecular mechanisms underlying the disease state remain unclear. To elucidate the cellular and molecular defects of SCZD, we directly reprogrammed fibroblasts from SCZD patients into human induced pluripotent stem cells (hiPSCs) and subsequently differentiated these disorder-specific hiPSCs into neurons (SI Fig. 1). SCZD hiPSC neurons showed diminished neuronal connectivity in conjunction with decreased neurite number, PSD95-protein levels and glutamate receptor expression. Gene expression profiles of SCZD hiPSC neurons identified altered expression of many components of the cAMP and WNT signaling pathways. Key cellular and molecular elements of the SCZD phenotype were ameliorated following treatment of SCZD hiPSC neurons with the antipsychotic Loxapine. To date, hiPSC neuronal pathology has only been demonstrated in diseases characterized by both the loss of function of a single gene product and rapid disease progression in early childhood4–6. We now report hiPSC neuronal phenotypes and gene expression changes associated with SCZD, a complex genetic psychiatric disorder (SI Table 1).

Background

Understanding individual differences in the development of extra-pyramidal side effects (EPS) as a response to antipsychotic therapy is essential to individualize treatment.

Methods

We performed genome-wide association studies to search for genetic susceptibility to EPS. Our sample consists of 738 schizophrenia patients, genotyped for 492K SNPs. We studied three quantitative measures of antipsychotic adverse drug reactions, the Simpson-Angus scale (SAS) for parkinsonism, the Barnes akathisia rating scale, and the abnormal involuntary movement scale (AIMS) as well as a clinical diagnosis of probable tardive dyskinesia.

Results

Two SNPs for SAS, rs17022444 and rs2126709 with p=1.2×10-10 and p=3.8×10-7, respectively, and one for AIMS, rs7669317 with p=7.7×10-8, reached genome-wide significance (q-value <0.1). Rs17022444 and rs7669317 were located in intergenic regions and rs2126709 was located in ZNF202 on 11q24. Fourteen additional signals were potentially interesting (q-value <0.5). The ZNF202 is a transcriptional repressor controlling, among other genes, PLP1 which is the major protein in myelin. Mutations in PLP1 cause Pelizaeus-Merzbacher disease, which has parkinsonism as an occurring symptom. Altered mRNA expression of PLP1 is associated with schizophrenia.

Conclusions

Although our findings require replication and validation, this study demonstrates the potential of GWAS to discover genes and pathways that mediate adverse effects of antipsychotics.

Individuals with autism are more likely to carry rare inherited and de novo copy number variants (CNVs). However, further research is needed to establish which CNVs are causal and the mechanisms by which these CNVs influence autism. We examined genomic DNA of children with autism (N=41) and healthy controls (N=367) for rare CNVs using a high-resolution array comparative genomic hybridization platform. We show that individuals with autism are more likely to harbor rare CNVs as small as ∼10 kb, a threshold not previously detectable, and that CNVs in cases disproportionately affect genes involved in transcription, nervous system development, and receptor activity. We also show that a subset of genes that have known or suspected allele-specific or imprinting effects and are within rare-case CNVs may undergo loss of transcript expression. In particular, expression of CNTNAP2 and ZNF214 are decreased in probands compared with their unaffected transmitting parents. Furthermore, expression of PRODH and ARID1B, two genes affected by de novo CNVs, are decreased in probands compared with controls. These results suggest that for some genes affected by CNVs in autism, reduced transcript expression may be a mechanism of pathogenesis during neurodevelopment.

Recent studies have established an important role for rare genomic deletions and duplications in the etiology of schizophrenia. This research suggests that the genetic architecture of neuropsychiatric disorders includes a constellation of rare mutations in many different genes. Mutations that confer substantial risk for schizophrenia have been identified at several loci, most of which have also been implicated in other neurodevelopmental disorders, including autism. Genetic heterogeneity is a characteristic of schizophrenia; conversely, phenotypic heterogeneity is a characteristic of all schizophrenia-associated mutations. Both kinds of heterogeneity probably reflect the complexity of neurodevelopment. Research strategies must account for both genetic and clinical heterogeneity to identify the genes and pathways crucial for the development of neuropsychiatric disorders.

Rare copy number variants (CNVs) play a prominent role in the etiology of schizophrenia and other neuropsychiatric disorders1. Substantial risk for schizophrenia is conferred by large (>500 kb) CNVs at several loci, including microdeletions at 1q21.1 2, 3q29 3, 15q13.3 2 and 22q11.2 4 and microduplication at 16p11.2 5. However, these CNVs collectively account for a small fraction (2-4%) of cases, and the relevant genes and neurobiological mechanisms are not well understood. Here we performed a large two-stage genome-wide scan of rare CNVs and report the significant association of copy number gains at chromosome 7q36.3 with schizophrenia (P= 4.0×10-5, OR = 16.14 [3.06, ∞]). Microduplications with variable breakpoints occurred within a 362 kb region and were detected in 29 of 8,290 (0.35%) patients versus two of 7,431 (0.03%) controls in the combined sample (p-value= 5.7×10-7, odds ratio (OR) = 14.1 [3.5, 123.9]). All duplications overlapped or were located within 89 kb upstream of the vasoactive intestinal peptide receptor VIPR2. VIPR2 transcription and cyclic-AMP signaling were significantly increased in cultured lymphocytes from patients with microduplications of 7q36.3. These findings implicate altered VIP signaling in the pathogenesis of schizophrenia and suggest VIPR2 as a potential target for the development of novel antipsychotic drugs.

The reduced expression of the Sp4 gene in Sp4 hypomorphic mice resulted in subtle vacuolization in the hippocampus as well as deficits in sensorimotor gating and contextual memory, putative endophenotypes for schizophrenia and other psychiatric disorders. In this study, we examined both spatial learning/memory and hippocampal long-term potentiation (LTP) of Sp4 hypomorphic mice. Impaired spatial learning/memory and markedly reduced LTP were found. To corroborate the functional studies, the expression of N-methyl-D-aspartate (NMDA) glutamate receptors was investigated with both western blot and immunohistochemical analyses. The reduced expression of the Sp4 gene decreased the level of the NR1 subunit of NMDA receptors in Sp4 hypomorphic mice. In human, SP4 gene was found to be deleted sporadically in schizophrenia patients, corroborating evidence that polymorphisms of human SP4 gene are associated with schizophrenia and other psychiatric disorders. Impaired NMDA neurotransmission has been implicated in several human psychiatric disorders. As yet, it remains unclear how mutations of candidate susceptibility genes for these disorders may contribute to the disruption of NMDA neurotransmission. Sp4 hypomorphic mice could therefore serve as a genetic model to investigate impaired NMDA functions resulting from loss-of-function mutations of human SP4 gene in schizophrenia and/or other psychiatric disorders. Furthermore, aberrant expression of additional genes, besides NMDAR1, likely also contributes to the behavioral abnormalities in Sp4 hypomorphic mice. Thus, further investigation of the Sp4 pathway may provide novel insights in our understanding of a variety of neuropsychiatric disorders.

Accurate information on haplotypes and diplotypes (haplotype pairs) is required for population-genetic analyses; however, microarrays do not provide data on a haplotype or diplotype at a copy number variation (CNV) locus; they only provide data on the total number of copies over a diplotype or an unphased sequence genotype (e.g., AAB, unlike AB of single nucleotide polymorphism). Moreover, such copy numbers or genotypes are often incorrectly determined when microarray signal intensities derived from different copy numbers or genotypes are not clearly separated due to noise. Here we report an algorithm to infer CNV haplotypes and individuals’ diplotypes at multiple loci from noisy microarray data, utilizing the probability that a signal intensity may be derived from different underlying copy numbers or genotypes. Performing simulation studies based on known diplotypes and an error model obtained from real microarray data, we demonstrate that this probabilistic approach succeeds in accurate inference (error rate: 1–2%) from noisy data, whereas previous deterministic approaches failed (error rate: 12–18%). Applying this algorithm to real microarray data, we estimated haplotype frequencies and diplotypes in 1486 CNV regions for 100 individuals. Our algorithm will facilitate accurate population-genetic analyses and powerful disease association studies of CNVs.

We tested the hypothesis that de novo copy number variation (CNV) is associated with autism spectrum disorders (ASDs). We performed comparative genomic hybridization (CGH) on the genomic DNA of patients and unaffected subjects to detect copy number variants not present in their respective parents. Candidate genomic regions were validated by higher-resolution CGH, paternity testing, cytogenetics, fluorescence in situ hybridization, and microsatellite genotyping. Confirmed de novo CNVs were significantly associated with autism (P = 0.0005). Such CNVs were identified in 12 out of 118 (10%) of patients with sporadic autism, in 2 out of 77 (3%) of patients with an affected first-degree relative, and in 2 out of 196 (1%) of controls. Most de novo CNVs were smaller than microscopic resolution. Affected genomic regions were highly heterogeneous and included mutations of single genes. These findings establish de novo germline mutation as a more significant risk factor for ASD than previously recognized.

Recent studies suggest that copy number polymorphisms (CNPs) may play an important role in disease susceptibility and onset. Currently, the detection of CNPs mainly depends on microarray technology. For case-control studies, conventionally, subjects are assigned to a specific CNP category based on the continuous quantitative measure produced by microarray experiments, and cases and controls are then compared using a chi-square test of independence. The purpose of this work is to specify the likelihood ratio test statistic (LRTS) for case-control sampling design based on the underlying continuous quantitative measurement, and to assess its power and relative efficiency (as compared to the chi-square test of independence on CNP counts). The sample size and power formulas of both methods are given. For the latter, the CNPs are classified using the Bayesian classification rule. The LRTS is more powerful than this chi-square test for the alternatives considered, especially alternatives in which the at-risk CNP categories have low frequencies. An example of the application of the LRTS is given for a comparison of CNP distributions in individuals of Caucasian or Taiwanese ethnicity, where the LRTS appears to be more powerful than the chi-square test, possibly due to misclassification of the most common CNP category into a less common category.

Genomic libraries derived from environmental DNA (metagenomic libraries) are useful for characterizing uncultured microorganisms. However, conventional library-screening techniques permit characterization of relatively few environmental clones. Here we describe a novel approach for characterization of a metagenomic library by hybridizing the library with DNA from a set of groundwater isolates, reference strains, and communities. A cosmid library derived from a microcosm of groundwater microorganisms was used to construct a microarray (COSMO) containing ∼1-kb PCR products amplified from the inserts of 672 cosmids plus a set of 16S ribosomal DNA controls. COSMO was hybridized with Cy5-labeled genomic DNA from each bacterial strain, and the results were compared with the results for a common Cy3-labeled reference DNA sample consisting of a composite of genomic DNA from multiple species. The accuracy of the results was confirmed by the preferential hybridization of each strain to its corresponding rDNA probe. Cosmid clones were identified that hybridized specifically to each of 10 microcosm isolates, and other clones produced positive results with multiple related species, which is indicative of conserved genes. Many clones did not hybridize to any microcosm isolate; however, some of these clones hybridized to community genomic DNA, suggesting that they were derived from microbes that we failed to isolate in pure culture. Based on identification of genes by end sequencing of 17 such clones, DNA could be assigned to functions that have potential ecological importance, including hydrogen oxidation, nitrate reduction, and transposition. Metagenomic profiling offers an effective approach for rapidly characterizing many clones and identifying the clones corresponding to unidentified species of microorganisms.